journal article Open Access Sep 01, 2023

Occlusion and multi-scale pedestrian detection A review

Array Vol. 19 pp. 100318 · Elsevier BV
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References
139
[1]
Wang "Learning person Re-identification models from videos with weak supervision" IEEE Trans Image Process (2021) 10.1109/tip.2021.3056223
[2]
Wang "A comprehensive overview of person Re-identification approaches" IEEE Access (2020) 10.1109/access.2020.2978344
[3]
Xu "A real-time, continuous pedestrian tracking and positioning method with multiple coordinated overhead-view cameras" Measurement (2021)
[4]
Dimitrievski "Behavioral pedestrian tracking using a camera and LiDAR sensors on a moving vehicle" Sensors (2019) 10.3390/s19020391
[5]
Wang "GraphTCN: spatio-temporal interaction modeling for human trajectory prediction" (2021)
[6]
Xue "PoPPL: pedestrian trajectory prediction by LSTM with automatic route class clustering" IEEE Transact Neural Networks Learn Syst (2021) 10.1109/tnnls.2020.2975837
[7]
Mhalla "An embedded computer-vision system for multi-object detection in traffic surveillance" IEEE Trans Intell Transport Syst (2019) 10.1109/tits.2018.2876614
[8]
Yang "Intelligent video analysis: a Pedestrian trajectory extraction method for the whole indoor space without blind areas" Computer Vision And Image Understanding (2020)
[9]
Du "Group surfing: a pedestrian-based approach to sidewalk robot navigation" (2019)
[10]
Li "FPGA implementation of real-time pedestrian detection using normalization-based validation of adaptive features clustering" IEEE Trans Veh Technol (2020) 10.1109/tvt.2020.2976958
[11]
Robin "Multi-robot target detection and tracking: taxonomy and survey" Aut Robots (2016) 10.1007/s10514-015-9491-7
[12]
Qiao "Research on abnormal pedestrian trajectory detection of dynamic crowds in public scenarios" IEEE Sensor J (2021) 10.1109/jsen.2021.3105680
[13]
Detecting Pedestrians Using Patterns of Motion and Appearance

Paul Viola, Michael J. Jones, Daniel Snow

International Journal of Computer Vision 2005 10.1007/s11263-005-6644-8
[14]
Dalal "Histograms of oriented gradients for human detection" (2005)
[15]
Dollar "Integral channel features" (2009)
[16]
Redmon "You only look once: unified, real-time object detection" (2016)
[17]
Redmon (2017)
[18]
Redmon (2018)
[19]
Liu "SSD: single shot multibox detector" (2016)
[20]
Girshick "Rich feature hierarchies for accurate object detection and semantic segmentation" (2014)
[21]
Girshick "Fast R-CNN" (2015)
[22]
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick et al.

IEEE Transactions on Pattern Analysis and Machine... 2017 10.1109/tpami.2016.2577031
[23]
Cai "A unified multi-scale deep convolutional neural network for fast object detection" (2016)
[24]
Bochkovskiy (2020)
[25]
Liu (2019)
[26]
Li "Scale-aware fast R-CNN for pedestrian detection" IEEE Trans Multimed (2018)
[27]
Dollar (2009)
[28]
Geiger "Are we ready for autonomous driving? the KITTI vision benchmark suite" (2012)
[29]
Zhang "CityPersons: a diverse dataset for pedestrian detection" (2017)
[30]
Li "A novel architecture of pedestrian detection" (2019) 10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00212
[31]
Kumar "A robust mRMR based pedestrian detection approach using shape descriptor" Trait Du Signal (2019) 10.18280/ts.360110
[32]
Yang "G2P: a new descriptor for pedestrian detection" Neural Comput Appl (2020) 10.1007/s00521-018-3815-4
[33]
Lian "Pedestrian detection using quaternion gradient based weber local descriptor" IEEE Access (2021) 10.1109/access.2021.3063294
[34]
Pfeifer "Shearlet features for pedestrian detection" J Math Imag Vis (2019) 10.1007/s10851-018-0834-9
[35]
Jiang "A pedestrian detection method based on genetic algorithm for optimize XGBoost training parameters" IEEE Access (2019) 10.1109/access.2019.2936454
[36]
Xie "A novel descriptor for pedestrian detection based on multi-layer feature fusion" (2020)
[37]
Kumar "A heuristic SVM based pedestrian detection approach employing shape and texture descriptors" Multimed Tool Appl (2020) 10.1007/s11042-020-08864-z
[38]
Zhou "Research on pedestrian detection technology based on the SVM classifier trained by HOG and LTP features" Future Generation Computer Systems-the International Journal Of Escience (2021) 10.1016/j.future.2021.06.016
[39]
Liu "A shallow-deep feature fusion method for pedestrian detection" Applied Sciences-Basel (2021)
[40]
Liu "High-level semantic feature detection: a new perspective for pedestrian detection" (2019)
[41]
Zhang (2022)
[42]
Cao "Pedestrian detection algorithm for intelligent vehicles in complex scenarios" Sensors (2020) 10.3390/s20133646
[43]
Lv "YOLOv5-AC: attention mechanism-based lightweight YOLOv5 for track pedestrian detection" Sensors (2022) 10.3390/s22155903
[44]
Liu "Efficient single-stage pedestrian detector by asymptotic localization fitting and multi-scale context encoding" IEEE Trans Image Process (2020) 10.1109/tip.2019.2938877
[45]
Saeidi "High-performance and deep pedestrian detection based on estimation of different parts" J Supercomput (2021) 10.1007/s11227-020-03345-4
[46]
Murthy "Optimized MobileNet plus SSD: a real-time pedestrian detection on a low-end edge device" International Journal Of Multimedia Information Retrieval (2021) 10.1007/s13735-021-00212-7
[47]
Zhang "Variational pedestrian detection" (2021)
[48]
Brazil "Pedestrian detection with autoregressive network phases" (2019)
[49]
Fu "See extensively while focusing on the core area for pedestrian detection" IEEE Access (2019) 10.1109/access.2019.2901270
[50]
Ren "A new multi-scale pedestrian detection algorithm in traffic environment" Journal Of Electrical Engineering & Technology (2021) 10.1007/s42835-021-00673-0

Showing 50 of 139 references

Metrics
23
Citations
139
References
Details
Published
Sep 01, 2023
Vol/Issue
19
Pages
100318
License
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Funding
National Natural Science Foundation of China Award: 51874300
Cite This Article
Wei Chen, Yuxuan Zhu, Zijian Tian, et al. (2023). Occlusion and multi-scale pedestrian detection A review. Array, 19, 100318. https://doi.org/10.1016/j.array.2023.100318
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